Adrià Casamitjana, Matteo Mancini, E. A. G. Robinson, Loïc Peter, Roberto Annunziata, Juri Althonayan, Shauna Crampsie, Emily Blackburn, Benjamin Billot, Alessia Atzeni, Oula Puonti, Yaël Balbastre, Peter J. Schmidt, James E Hughes, Jean C. Augustinack, Brian L. Edlow, Lilla Zöllei, David L. Thomas, Dorit Kliemann, Martina Bocchetta, Catherine Strand, Janice L. Holton, Zane Jaunmuktane, Juan Eugenio Iglesias
provide exquisite three-dimensional cytoarchitectural maps but lack probabilistic labels throughout the whole brain: that is, the likelihood of each location belonging to a given ROI. Here we present NextBrain, a probabilistic histological atlas of the whole human brain. We developed artificial intelligence-enabled methods to align roughly 10,000 histological sections from five whole brain hemispheres into three-dimensional volumes and to produce delineations for 333 ROIs on these sections. We also created a companion Bayesian tool for automatic segmentation of these ROIs in magnetic resonance imaging (MRI) scans. We showcase two applications of the atlas: segmentation of ultra-high-resolution ex vivo MRI and volumetric analysis of Alzheimer's disease using in vivo MRI. We publicly release raw and aligned data, an online visualization tool, the atlas, the segmentation tool, and ground truth delineations for a high-resolution ex vivo hemisphere used in validation. By enabling researchers worldwide to automatically analyse brain MRIs at a higher level of granularity, NextBrain holds promise to increase the specificity of findings and accelerate our quest to understand the human brain in health and disease.